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Category: transportation

New technology from Stanford scientists finds long-hidden quakes, and possible clues about how earthquakes evolve.

Tiny movements in Earth’s outermost layer may provide a Rosetta Stone for deciphering the physics and warning signs of big quakes. New algorithms that work a little like human vision are now detecting these long-hidden microquakes in the growing mountain of seismic data.

Measures of Earth’s vibrations zigged and zagged across Mostafa Mousavi’s screen one morning in Memphis, Tenn. As part of his PhD studies in geophysics, he sat scanning earthquake signals recorded the night before, verifying that decades-old algorithms had detected true earthquakes rather than tremors generated by ordinary things like crashing waves, passing trucks or stomping football fans.

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Alibaba is one of the best places around to find the coolest and sometimes weirdest electric vehicles in the world. As part of a new series known as Awesomely weird Alibaba electric vehicle of the week, we’re taking a look at some of our favorites.

This week’s feature is a small-yet-mighty electric pickup truck designed for utility and off-road usage, though it may even be street legal as an NEV in the US.

If the proportions look at bit odd on this electric pickup truck, that’s because they are.

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From self-driving cars, to the many automated production processes we will end up creating; we will allow AI drive us into the next era of human civilization.

We will allow the creation to create, and according to futurist and technologists’ world over, there is only one likely path where this road will lead to — the Singularity (the point where computer intelligence surpasses human intelligence).

- The Above is an excerpt from the book, 2020s & The Future Beyond.

Will be happy to hear the thoughts of group members.

#Iconickelx.

#AI #Singularity #Future

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I like this idea. I don’t want AI to be a black box, I want to know what’s happening and how its doing it.

The field of artificial intelligence has created computers that can drive cars, synthesize chemical compounds, fold proteins, and detect high-energy particles at a superhuman level.

However, these AI algorithms cannot explain the thought processes behind their decisions. A computer that masters protein folding and also tells researchers more about the rules of biology is much more useful than a computer that folds proteins without explanation.

Therefore, AI researchers like me are now turning our efforts toward developing AI algorithms that can explain themselves in a manner that humans can understand. If we can do this, I believe that AI will be able to uncover and teach people new facts about the world that have not yet been discovered, leading to new innovations.

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Circa 2018

Riding the wind above the Andes Mountains, an experimental glider has set a world record for high-altitude flight.

On Sept. 2, the sleek Perlan 2 glider carried two pilots to 76100 feet, or more than 14 miles, over the El Calafate region in southern Argentina. That’s the highest altitude ever reached by humans aboard an unpowered fixed-wing aircraft, and one of the highest altitudes reached by an aircraft of any description. Only spy planes and specialized balloons have flown higher.

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A new method to reason about uncertainty might help artificial intelligence to find safer options faster, for example in self-driving cars, according to a new study to be published shortly in AAAI involving researchers at Radboud University, the University of Austin, the University of California, Berkeley, and the Eindhoven University of Technology.

The researchers have defined a new approach to so-called ‘uncertain partially observable Markov decision processes, or uPOMDPs. In layman’s terms, these are models of the real world that estimate the probability of events. A car, for example, will face many unknown situations when it starts driving. To validate the of self-driving cars, extensive calculations are run to analyze how the AI would approach various situations. The researchers argue that with their new approach, these modeling exercises can become far more realistic, and thus allows AI to make better, safer decisions quicker.

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